Some neuralphysiological data acquisition systems are configured to record and analyze animal or human brain and/or peripheral-nerve electrical activity. Such systems typically include one or more sensors that generate neural signals indicative of the brain or peripheral-nerve electrical activity near the sensor. Neural signals generated by the sensors can be collected and processed to assist in the study of, for example, sensory perception, motor control, learning and memory, attention, cognition and decision making, drug and toxin effects, epilepsy, Parkinson's, neuroprosthetics, brain-machine interfaces, neurostimulation therapies, dystonia, traumatic brain injury, and stroke.
In some instances, a power supply of the neuralphysiological data acquisition system may add noise to the neural signals that can interfere with the processing and use of the neural signals. For example, when the neuralphysiological data acquisition system is plugged into a wall socket to access mains electricity, e.g., a general-purpose alternating current (“AC”) electric power supply, the line frequency of the mains electricity can manifest itself as noise that combines with the neural signals. Noise resulting from the line frequency of the mains electricity or other power supply is an example of electrical line noise.
In the United States and various other countries, the mains electricity has a nominal line frequency of 60 Hz. In many other countries in the world, the mains electricity has a nominal line frequency of 50 Hz. In both cases, the actual line frequency of the mains electricity at any given time is typically somewhere within a range defined by the nominal line frequency plus or minus a frequency deviation. In the United States, for instance, the actual line frequency at any given time is typically within a range defined as 60 Hz±3 Hz.
Thus, the actual frequency of electrical line noise in neural signals collected by a neuralphysiological data acquisition system is not constant and can therefore be difficult to filter from the neural signals.